TDWI Checklist Report: Cloud Data Warehousing

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tdwi.org 9 TDWI RESE ARCH T D W I C H E C K L I S T R E P O R T: C LO U D DATA WA R E H O U S I N G S T R A I G H T TA L K 7 UNDERSTANDING HYBRID CLOUD Hybrid cloud architectures hold promise when an organization has a clear understanding of the key performance criteria and how the architecture is designed to optimize for those criteria. Yet as the structure and offerings of hybrid cloud environments continue to grow in complexity, your data architects will require more scaffolding to maintain visibility across the landscape. We suggest that hybrid cloud data warehouse architectures require more sophisticated supporting technologies. We recommend introducing platform management technologies that optimize management across different platforms and provide guidance for allocating data and resource usage for optimal performance and value. These tools provide the necessary visibility to ensure optimal use of hybrid cloud architectures. Most organizations are set on a trajectory to migrate their reporting and analytics to the cloud by employing a combination of a cloud-based data warehouse, data lake, and data lakehouse concepts. Yet why should an organization limit itself to a single virtual environment with a specific cloud service provider? We are already seeing organizations migrating to more than one cloud environment using the same CSP and even employing services from multiple cloud service, SaaS, and PaaS providers. Different cloud service providers provide different services and capabilities, and the same economic and performance factors that are driving organizations to the cloud are often encouraging them to seek out the best of breed across a variety of CSPs and vendors for particular services and balance costs versus performance. That being said, some challenges and drawbacks to this approach remain, such as: • Increased data chaos due to unmanaged data distribution across a variety of CSP object stores • Difficulty in managing spiraling costs for data egress and replicated invocation of the same or similar services • Managing the inventory of data assets across on-premises and cloud storage resources • Managing data protection across the different platforms • Performance bottlenecks when a hybrid analytics application must move data from one CSP to another • Increased complexity of data integration, especially as data sets transition from one platform to another

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